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About

Cansu Soyleyici is a robotics researcher whose work focuses on bridging the gap between industrial automation and autonomous perception. Her primary research areas include 3-D surface reconstruction, sensor-guided robotic manipulation, and the development of open programming interfaces for commercial robots. In her most cited work, she designed a robotic system capable of autonomously reconstructing the 3-D surface of objects by fusing point cloud data from profile and field range sensors, addressing the challenge of limited sensor field-of-view through multi-view integration. She also developed a novel method for determining local coordinate frames attached to objects using a laser profile sensor mounted on an industrial robot, enabling precise spatial localization within cluttered workspaces. Additionally, Soyleyici contributed to the design of an application programming interface (API) for commercial industrial robots, aiming to overcome restrictive, proprietary programming environments and enable more flexible, concurrent process control. Her work, cited over a dozen times, is particularly relevant for researchers and engineers seeking to enhance the autonomy and programmability of industrial robotic systems.